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At least 721 records · Page 40

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NASA NTRS2001

Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging

OBJECTIVE: The objective of our study was to determine the effects of MR sequence (fluid-attenuated inversion-recovery [FLAIR], proton density--weighted, and T2-weighted) and of lesion location on sensitivity and specificity of lesion detection. MATERIALS AND METHODS: We generated FLAIR, proton density-weighted, and T2-weighted brain images with 3-mm lesions using published parameters for acute multiple sclerosis plaques. Each image contained from zero to five lesions that were distributed among cortical-subcortical, periventricular, and deep white matter regions; on either side; and anterior or posterior in position. We presented images of 540 lesions, distributed among 2592 image regions, to six neuroradiologists. We constructed a contingency table for image regions with lesions and another for image regions without lesions (normal). Each table included the following: the reviewer's number (1--6); the MR sequence; the side, position, and region of the lesion; and the reviewer's response (lesion present or absent [normal]). We performed chi-square and log-linear analyses. RESULTS: The FLAIR sequence yielded the highest true-positive rates (p < 0.001) and the highest true-negative rates (p < 0.001). Regions also differed in reviewers' true-positive rates (p < 0.001) and true-negative rates (p = 0.002). The true-positive rate model generated by log-linear analysis contained an additional sequence-location interaction. The true-negative rate model generated by log-linear analysis confirmed these associations, but no higher order interactions were added. CONCLUSION: We developed software with which we can generate brain images of a wide range of pulse sequences and that allows us to specify the location, size, shape, and intrinsic characteristics of simulated lesions. We found that the use of FLAIR sequences increases detection accuracy for cortical-subcortical and periventricular lesions over that associated with proton density- and T2-weighted sequences.

NASA Discipline Neuroscience↗

NASA NTRS2012

Submillimeter Follow-Up of WISE-Selected Hyperluminous Galaxies

We have used the Caltech Submillimeter Observatory (CSO) to follow-up a sample of Wide-field Infrared Survey Explorer (WISE) selected, hyperluminous galaxies, the so-called W1W2-dropout galaxies. This is a rare (approx.1000 all-sky) population of galaxies at high redshift (peaks at z = 2-3), which are faint or undetected by WISE at 3.4 and 4.6 microns, yet are clearly detected at 12 and 22 microns. The optical spectra of most of these galaxies show significant active galactic nucleus activity. We observed 14 high-redshift (z > 1.7) W1W2-dropout galaxies with SHARC-II at 350-850 microns, with nine detections, and observed 18 with Bolocam at 1.1 mm, with five detections. Warm Spitzer follow-up of 25 targets at 3.6 and 4.5 microns, as well as optical spectra of 12 targets, are also presented in the paper. Combining WISE data with observations from warm Spitzer and CSO, we constructed their mid-IR to millimeter spectral energy distributions (SEDs). These SEDs have a consistent shape, showing significantly higher mid-IR to submillimeter ratios than other galaxy templates, suggesting a hotter dust temperature.We estimate their dust temperatures to be 60 C120 K using a single-temperature model. Their infrared luminosities are well over 10(exp 13) Stellar Luminosity. These SEDs are not well fitted with existing galaxy templates, suggesting they are a new population with very high luminosity and hot dust. They are likely among the most luminous galaxies in the universe.We argue that they are extreme cases of luminous, hot dust-obscured galaxies (DOGs), possibly representing a short evolutionary phase during galaxy merging and evolution. A better understanding of their long-wavelength properties needs ALMA as well as Herschel data.

Wu, Jingwen↗

NASA NTRS2013

Submillimeter Follow-up of Wise-Selected Hyperluminous Galaxies

We have used the Caltech Submillimeter Observatory (CSO) to follow-up a sample of Wide-field Infrared Survey Explorer (WISE) selected, hyperluminous galaxies, the so-called W1W2-dropout galaxies. This is a rare (approximately 1000 all-sky) population of galaxies at high redshift (peaks at zeta = 2-3), which are faint or undetected by WISE at 3.4 and 4.6 micrometers, yet are clearly detected at 12 and 22 micrometers. The optical spectra of most of these galaxies show significant active galactic nucleus activity. We observed 14 high-redshift (zeta greater than 1.7) W1W2-dropout galaxies with SHARC-II at 350-850 micrometers, with nine detections, and observed 18 with Bolocam at 1.1 mm, with five detections. Warm Spitzer follow-up of 25 targets at 3.6 and 4.5 micrometers, as well as optical spectra of 12 targets, are also presented in the paper. Combining WISE data with observations from warm Spitzer and CSO, we constructed their mid-IR to millimeter spectral energy distributions (SEDs). These SEDs have a consistent shape, showing significantly higher mid-IR to submillimeter ratios than other galaxy templates, suggesting a hotter dust temperature.We estimate their dust temperatures to be 60-120 K using a single-temperature model. Their infrared luminosities are well over 10(exp 13) solar luminosity. These SEDs are not well fitted with existing galaxy templates, suggesting they are a new population with very high luminosity and hot dust. They are likely among the most luminous galaxies in the universe.We argue that they are extreme cases of luminous, hot dust-obscured galaxies (DOGs), possibly representing a short evolutionary phase during galaxy merging and evolution. A better understanding of their long-wavelength properties needs ALMA as well as Herschel data.

Wu, Jingwen↗

NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Crespo, Luis G.↗

NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Crespo, Luis G.↗

NASA NTRS1973

A New GaAs Laser Radar for Atmospheric Measurements

A special GaAs lidar using fiber coupled diode lasers was constructed for the purpose of measuring the extinction coefficient distribution within a large atmospheric volume at a rate compatible with atmospheric kinematics. The technique is based on taking backscatter signature ratios over spatial increments after the returns are normalized by pulse integration. Essential aspects of the lidar design are beam pulse power, repetition rate, detection system dynamic range and decay linearity. It was necessary to preclude the possibility of eye hazard under any operating conditions, including directly viewing the emitting aperture at close distance with a night-adapted eye. The electronic signal processing and control circuits were built to allow versatile operations. Extinction coefficient measurements were made in fog and clouds using a low-power laboratory version of the lidar, demonstrating feasibility. Data are presented showing range squared corrected backscatter profiles converted to extinction coefficient profiles, temporal signal fluctuations, and solar induced background noise. These results aided in the design of the lidar which is described. Functional tests of this lidar and the implications relevant to the design of a prototype model are discussed. This work was jointly sponsored by Sperry Rand Corporation under its Independent Research and Development program; the Air Force Avionics Laboratory, Wright Field, Dayton, Ohio; and the Naval Ammunition Depot, Crane, Indiana.

Brown, R. T.↗

DOE OSTI2015

Building America Case Study: Calculating Design Heating Loads for Superinsulated Buildings, Ithaca, New York; Technology Solutions for New and Existing Homes, Energy Efficiency & Renewable Energy (EERE)

Designing a superinsulated home has many benefits including improved comfort, reduced exterior noise penetration, lower energy bills, and the ability to withstand power and fuel outages under much more comfortable conditions than a typical home. Extremely low heating and cooling loads equate to much smaller HVAC equipment than conventionally required. Sizing the mechanical system to these much lower loads reduces first costs and the size of the distribution system needed. While these homes aren't necessarily constructed with excessive mass in the form of concrete floors and walls, the amount of insulation and the increase in the thickness of the building envelope can lead to a mass effect, resulting in the structures ability to store much more heat than a code built home. This results in a very low thermal inertia making the building much less sensitive to drastic temperature swings thereby decreasing the peak heating load demand. Alternative methods that take this inertia into account along with solar and internal gains result in smaller more appropriate design loads than those calculated using Manual J version 8. During the winter of 2013/2014, CARB monitored the energy use of three homes in climate zone 6 in an attempt to evaluate the accuracy of two different mechanical system sizing methods for low load homes. Based on the results, it is recommended that internal and solar gains be included and some credit for thermal inertia be used in sizing calculations for superinsulated homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Technology Solutions Case Study: Calculating Design Heating Loads for Superinsulated Buildings

Designing a superinsulated home has many benefits including improved comfort, reduced exterior noise penetration, lower energy bills, and the ability to withstand power and fuel outages under much more comfortable conditions than a typical home. Extremely low heating and cooling loads equate to much smaller HVAC equipment than conventionally required. Sizing the mechanical system to these much lower loads reduces first costs and the size of the distribution system needed. While these homes aren't necessarily constructed with excessive mass in the form of concrete floors and walls, the amount of insulation and the increase in the thickness of the building envelope can lead to a mass effect, resulting in the structures ability to store much more heat than a code built home. This results in a very low thermal inertia making the building much less sensitive to drastic temperature swings thereby decreasing the peak heating load demand. Alternative methods that take this inertia into account along with solar and internal gains result in smaller more appropriate design loads than those calculated using Manual J version 8. During the winter of 2013/2014, the Consortium for Advanced Residential Buildings team monitored the energy use of three homes in climate zone 6 in an attempt to evaluate the accuracy of two different mechanical system sizing methods for low load homes. Based on the results, it is recommended that internal and solar gains be included and some credit for thermal inertia be used in sizing calculations for superinsulated homes.

Building America↗

NASA NTRS1990

Control of multiple resonant power processors in a multi-source system

Analysis and test results show that phasor-regulated, Mapham-derived resonant inverters can be paralleled to provide standardizing interfaces for multiple sources on a utility-type, aerospace power distribution bus. The basic sources do not require matching in any way, and may have grossly different characteristics. Fully stable system architectures with multiple sources, parallel/redundant distribution buses, and a wide variety of loads can be easily constructed and controlled. The commands and parameters available for system control allow for tight tolerance bus voltage control, and absolute power-sharing control from the various sources over the full range of possible source and load variations. That level of control enables simplified load power processing hardware and the distribution of losses to optimally load the source thermal control system. Positive control of all system performance and allocation of losses are not required by all missions or vehicles, and overall vehicle considerations do not always require the loads on vehicle energy sources and thermal control systems to be balanced. In those cases, power system control can be simplified, and a hierarchical set of defaults can be substituted for computer-generated or supervisory input commands to allow for stable, fully autonomous system operation.

Mildice, James↗

DOE OSTI2018

LCLS-II Cryomodule and Cryogenic Distribution Control

LCLS-II is a superconducting upgrade to the existing Linear Coherent Light Source at the SLAC National Accelerator Laboratory. Construction is underway with a planned continuous wave beam rate of up to 1 MHz. Two cryogenic plants provide helium to a distribution system, and 37 cryomodules with superconducting cavities will operate with Liquid helium at 2.2K. The cryomodules and distribution system is controlled with networked PLC's and EPICS as an integrated system that work in concert for controlling valves, pressure, flow, and temperature. Interlocks and critical process information is communicated with the Low Level Radio Frequency, vacuum, and magnet systems. Engaging the controls community proved vital in advancing the controls architecture from a conventional design to a centralized, reliable, and cost-effective distributed platform.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Resolving crystallographic geometrically necessary dislocations in three dimensions in a hexagonal close packed titanium alloy

Abstract Geometrically necessary dislocation (GND) content is measured from mm 3 -scaled Ti7Al three-dimensional (3D) microstructural data using a theory extended for hexagonal close packed crystals, which accounts for basal, prismatic and pyramidal ⟨ c + a ⟩ type dislocation content. The Ti7Al samples have been mechanically pre-strained to two different strain levels, and will then be strained along the same axis in uniaxial tension during simulation. Both inter- and intragranular GNDs across the microstructures have been characterized, with a large contribution of pyramidal ⟨ c + a ⟩ GNDs, consistent with the relative slip activity involved in pre-straining. The spatially resolved crystallographic GND distributions within the 3D microstructures are used to instantiate a microstructure model for forward modeling deformation simulations by a dislocation density hardening elasto-viscoplastic fast Fourier transform framework. Coarsening the voxel resolution during the initial microstructure construction procedure is shown to strongly impact both the magnitude and spatial distribution of the GNDs and in turn the forward deformation response of the pre-strained material. This study indicates that the voxel resolution desired when transferring from measured to model microstructures need not only be proportionally scaled with the microstructure but also sufficiently fine to capture the subgranular orientation gradients that may already be present in the material.

Materials Science↗

DOE OSTI2019

System of ideal quantum dots with Coulomb interaction

The wave functions of single-electron states localised on a system of single-level ideal quantum dots in a semiconductor matrix are constructed. The standard Kane theory, which describes the renormalisation of the effective mass of electrons in bulk III − V semiconductors, is transformed, for the first time as far as we know, for small-size quantum dots. The renormalised electron mass in a quantum dot depends on its ground state energy, which, in turn, depends on this mass. Thus, a self-consistent problem is obtained for calculating the electron binding energy. The radius of the Debye screening of the Coulomb interaction in a system of quantum dots is calculated at room temperature. The Coulomb repulsion of electrons localised on dots limits from above the possible number of filled dots. The condition is formulated for the optimal concentration of quantum dots. A classical distribution function for the probability of quantum dot filling is constructed. It is found the state, where electrons fill exactly half the maximum possible number of filled dots, exhibits the minimal energy (and therefore the most stable), the condition being fairly universal. In particular, it can be used to estimate the limiting efficiency of quantum-dot diode lasers. (quantum dots)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

The fungus that came in from the cold: dry rot’s pre-adapted ability to invade buildings

Many organisms benefit from being pre-adapted to niches shaped by human activity, and have successfully invaded man-made habitats. One such species is the dry rot fungus Serpula lacrymans, which has a wide distribution in buildings in temperate and boreal regions, where it decomposes coniferous construction wood. Comparative genomic analyses and growth experiments using this species and its wild relatives revealed that S. lacrymans evolved a very effective brown rot decay compared to its wild relatives, enabling an extremely rapid decay in buildings under suitable conditions. Adaptations in intracellular transport machineries promoting hyphal growth, and nutrient and water transport may explain why it is has become a successful invader of timber in houses. Further, we demonstrate that S. lacrymans has poor combative ability in our experimental setup, compared to other brown rot fungi. In sheltered indoor conditions, the dry rot fungus may have limited encounters with other wood decay fungi compared to its wild relatives. Overall, our analyses indicate that the dry rot fungus is an ecological specialist with poor combative ability against other fungi.

fungal biology↗

NASA NTRS1988

A reference standard for bidirectional reflection distribution function and bidirectional transmission distribution function measurement

A Lambertian reference standard for uniformly scattering a beam of light is constructed of a plate having a planar surface with a layer of glue disposed on the surface. An evenly packed layer of monodisperse spheres is set in the layer, and when the standard is used for bi-directional (BRDF) measurements, the spheres are coated with a layer of highly relective substance, such as gold or silver. When the standard is used for bi-directional transmittance distribution function (BTDF) measurements, the spheres are of a transparent material and are provided with a roughened surface, as by acid etching. In this case, the layer of glue is an optical cement, and the plate is of glass, with the spheres, the layer, and the plate all possessing a similar refractive index.

Witherow, William K.↗

DOE OSTI2017

An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

We describe an emulator of a detailed cloud parcel model which has been trained to assess droplet nucleation from a complex, multimodal aerosol size distribution simulated by a global aerosol–climate model. The emulator is constructed using a sensitivity analysis approach (polynomial chaos expansion) which reproduces the behavior of the targeted parcel model across the full range of aerosol properties and meteorology simulated by the parent climate model. An iterative technique using aerosol fields sampled from a global model is used to identify the critical aerosol size distribution parameters necessary for accurately predicting activation. Across the large parameter space used to train them, the emulators estimate cloud droplet number concentration (CDNC) with a mean relative error of 9.2% for aerosol populations without giant cloud condensation nuclei (CCN) and 6.9% when including them. Versus a parcel model driven by those same aerosol fields, the best-performing emulator has a mean relative error of 4.6%, which is comparable with two commonly used activation schemes also evaluated here (which have mean relative errors of 2.9 and 6.7%, respectively). We identify the potential for regional biases in modeled CDNC, particularly in oceanic regimes, where our best-performing emulator tends to overpredict by 7%, whereas the reference activation schemes range in mean relative error from -3 to 7%. The emulators which include the effects of giant CCN are more accurate in continental regimes (mean relative error of 0.3%) but strongly overestimate CDNC in oceanic regimes by up to 22%, particularly in the Southern Ocean. Finally, the biases in CDNC resulting from the subjective choice of activation scheme could potentially influence the magnitude of the indirect effect diagnosed from the model incorporating it.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1940

Stresses in single-spar wing constructions with incompletely built-up ribs

It is shown that the force distribution resulting from incomplete ribs in single spar wing structures may be determined with the aid of the shear field method by a statistically indeterminate computation. A numerical computation is given of the force distribution of a wing structure whose two neighboring incomplete ribs with web missing in half the section are torsionally loaded.

Reinitzhuber, F↗

NASA NTRS2019

Statistical Process Control and Capability Study on the Water Content Measurements in NASA Glenn's Icing Research Tunnel

The Icing Research Tunnel (IRT) at NASA Glenn Research Center follows the recommended practice for icing tunnel calibration outlined in SAE's ARP5905 document. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within in the specifications presented to customers that the variation is within +/- 10% of the calibrated, target measurement. With recent measurements and instrumentation errors, a more thorough assessment of error source was desired. By constructing statistical process control charts, the ability to determine how the instrument varies in the short term, mid term, and long term was gained. The control charts offer a view of instrument error, facility error, or installation changes. It was discovered that there was a shift from target to mean baseline thus leading to the study of the overall capability indices of the liquid water content measuring instrument to perform within specifications defined in the IRT. This presentation describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, Chauvenet's Criterion for rejection of data, distribution check of data, and mean, median and mode for construction of control charts. Further data is presented to describe the repeatability of the IRT with the Multi-Element Sensor and the ability to maintain a stable process for the defined calibration schedule.

Timko, Emily N.↗

DOE OSTI2021

The fate of carbon utilized by the subterranean termite Reticulitermes flavipes

Abstract Subterranean termites are ecosystem engineers that modulate the flow of carbon from dead wood to the atmosphere and soil, yet their contributions to the latter pool are largely unaccounted for in carbon cycling models. The fate of C from wood utilized by Reticulitermes flavipes (Kollar) was determined using a reductionist design in a closed system with δ 13 C labeled wood as a stable isotope tracer. The percentage of wood‐based carbon in termite respiratory gases, tissues, and organic deposits (frass and construction materials) was measured for five colonies to budget wood‐C mass distributed into metabolic and behavioral pathways during a 160‐h incubation period. We found that termites emitted 42% of the C from wood as gas (largely as carbon dioxide), returned 40% to the environment as organic deposits (frass and construction materials), and retained 18% in their tissues (whole alimentary tracts and de‐gutted bodies). Our findings affirm that termites are a source of greenhouse gases but are also ecosystem engineers that return approximately half the C from dead wood as organic deposits into their surrounding environment.

54 ENVIRONMENTAL SCIENCES↗